CN116017394A

CN116017394A - Data analysis method and device

Info

Publication number: CN116017394A
Application number: CN202211613161.9A
Authority: CN
Inventors: 谢涵; 王丹
Original assignee: Guangzhou Aipu Road Network Technology Co Ltd
Current assignee: Guangzhou Aipu Road Network Technology Co Ltd
Priority date: 2022-12-15
Filing date: 2022-12-15
Publication date: 2023-04-25

Abstract

The application provides a data analysis method and device, and relates to the technical field of communication. The method comprises the following steps: receiving a first data analysis request sent by the AF through the NEF, and respectively sending a first data acquisition request to the NF or the OAM, the H-ADRF and the V-NWDAF according to the first data analysis request, wherein the first data acquisition request comprises: a first data analysis identifier and a first analysis target; receiving first analysis data corresponding to a first analysis target and a first data analysis identifier sent by NF or OAM, H-ADRF and V-NWDAF, wherein the V-NWDAF acquires the first analysis data through V-ADRF; and carrying out preset analysis on the first analysis data according to the first data analysis identifier, and sending a first data analysis result to the AF through the NEF. The method and the device can realize data sharing among different service networks PLMNs, break through the space constraint of data and improve the data analysis and prediction performance.

Description

Data analysis method and device

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a data analysis method and apparatus.

Background

5G (5 th Generation Mobile Communication Technology, end of fifth generation mobile communication) is the core of the new generation information communication base, with faster rate, larger capacity and lower latency. Digital transformation based on 5G technology is being tightened, so that technologies such as big data, cloud computing and Internet of things are put into practice from concepts, and especially for big data, the popularization of 5G pushes the big data to a new height. The development of high-speed informatization makes data information explosively grow, and data types among people, objects and objects are more abundant, so that people can analyze useful information in massive data by utilizing various AI (Artificial Intelligence) or ML (Machine Learning) technologies, and the production and the life of people are served.

For big data, due to the limitation of various factors and the constraints of user privacy, data security, operator supervision and the like, the data is often limited to a specific space, which causes a certain trouble to the development of AI/ML technology.

When a UE (User Equipment) roams to a V-PLMN (Visit Public Land Mobile Network, visited public land mobile network) which has not been accessed before, if the UE needs to request a data analysis service in the V-PLMN, but there is no historical data information related to the UE in the V-PLMN, even if the V-PLMN starts to collect data after the registration of the UE, the collected data is very limited, so that the performance of analysis prediction is poor; the H-PLMN (Home Public Land Mobile Network ) accessed by the UE cannot acquire the data collected in the V-PLMN, resulting in a waste of data resources to some extent.

Disclosure of Invention

The invention aims to provide a data analysis method and a data analysis device aiming at the defects in the prior art so as to realize data sharing among different service networks PLMNs, break through the space constraint of data and improve the data analysis prediction performance.

In order to achieve the above purpose, the technical solution adopted in the embodiment of the present application is as follows:

In a first aspect, an embodiment of the present application provides a data analysis method applied to a home network data analysis function H-NWDAF, where the method includes:

receiving a first data analysis request sent by an Application Function (AF) through a network opening function (NEF), wherein the first data analysis request comprises: a first data analysis identifier and a first analysis target;

according to the first data analysis request, a first data acquisition request is sent to a network function NF or an operation maintenance management OAM, a home analysis data repository function H-ADRF and a visited network data analysis function V-NWDAF, respectively, where the first data acquisition request includes: the first data analysis identifier and the first analysis target;

receiving first analysis data corresponding to the first analysis target and the first data analysis identifier sent by the NF or the OAM, the H-ADRF and the V-NWDAF, wherein the V-NWDAF acquires the first analysis data through a visit place analysis data storage function V-ADRF;

and carrying out preset analysis on the first analysis data according to the first data analysis identifier, and sending a first data analysis result to the AF through the NEF.

Optionally, after performing a preset analysis on the first analysis data according to the first data analysis identifier and sending a data analysis result to the AF through the NEF, the method further includes:

And storing the first analysis data and the first data analysis result sent by the NF or the OAM and the V-NWDDAF to the H-ADRF.

Optionally, the method further comprises:

receiving a second data acquisition request sent by the V-NWDAF, wherein the second data acquisition request comprises: a second data analysis identifier and a second analysis target;

acquiring second analysis data corresponding to the second data analysis identifier and the second analysis target from the H-ADRF;

and sending the second analysis data to the V-NWDAF.

Optionally, the sending the second analysis data to the V-NWDAF includes:

randomly acquiring sample second analysis data from the second analysis data;

according to a preset algorithm, inserting synthesized second analysis data into the sample second analysis data to obtain expanded data;

extracting target second analysis data from the expanded data;

and sending the target second analysis data to the V-NWDAF.

In a second aspect, an embodiment of the present application further provides a data analysis method applied to a visited network data analysis function V-NWDAF, where the method includes:

receiving a first data acquisition request sent by a home network data analysis function H-NWDAF, where the first data acquisition request is generated by the H-NWDAF according to a first data analysis request, and the first data acquisition request includes: a first data analysis identifier and a first analysis target;

According to the first data acquisition request, acquiring first analysis data corresponding to the first data analysis identifier and the first analysis target from a visiting place analysis data storage function V-ADRF;

and sending the first analysis data to the H-NWDAF so that the H-NWDAF performs preset analysis on the first analysis data, and sending a data analysis result to the AF through a network opening function NEF.

Optionally, the sending the first analysis data to the H-NWDAF includes:

randomly acquiring sample first analysis data from the first analysis data;

according to a preset algorithm, inserting and synthesizing first analysis data into the first analysis data of the sample to obtain expanded data;

extracting target first analysis data from the expanded data;

and sending the target first analysis data to the V-NWDAF.

Optionally, the method further comprises:

receiving a second data analysis request sent by the application function AF through the network opening function NEF, wherein the second data analysis request comprises: a second data analysis identifier and a second analysis target;

and respectively sending a second data acquisition request to a network function NF or operation maintenance management OAM, a visit area analysis data storage function V-ADRF and the H-NWDAF according to the second data analysis request, wherein the second data acquisition request comprises: the second data analysis identity and the second analysis target;

Receiving second analysis data corresponding to the second analysis target and sent by the NF or the OAM, the V-ADRF and the H-NWDAF, wherein the H-NWDAF acquires the second analysis data through a home analysis data storage function H-ADRF;

and carrying out preset analysis on the second analysis data according to the second data analysis identifier, and sending a second data analysis result to the AF through the NEF.

Optionally, after the receiving the second analysis data corresponding to the second analysis target and the second data analysis identifier sent by the NF or the OAM, the V-ADRF, and the H-NWDAF, the method further includes:

and storing second analysis data and the second data analysis result sent by the NF or the OAM and the H-NWDDAF to the V-ADRF.

In a third aspect, an embodiment of the present application further provides a data analysis device applied to a home network data analysis function H-NWDAF, where the device includes:

the first analysis request receiving module is configured to receive a first data analysis request sent by the application function AF through the network open function NEF, where the first data analysis request includes: a first data analysis identifier and a first analysis target;

A first acquisition request sending module, configured to send a first data acquisition request to a network function NF or an operation maintenance management OAM, a home location analysis data repository function H-ADRF, and a visited network data analysis function V-NWDAF according to the first data analysis request, where the first data acquisition request includes: the first data analysis identifier and the first analysis target;

the first analysis data receiving module is used for receiving the first analysis data corresponding to the first analysis target and the first data analysis identifier sent by the NF or the OAM, the H-ADRF and the V-NWDAF, wherein the V-NWDAF acquires the first analysis data through a visit area analysis data storage function V-ADRF;

and the first data analysis module is used for carrying out preset analysis on the first analysis data according to the first data analysis identifier and sending a data analysis result to the AF through the NEF.

Optionally, after the first data analysis module, the apparatus further includes:

and the first data storage module is used for storing the first analysis data and the first data analysis result sent by the NF or the OAM and the V-NWDDAF to the H-ADRF.

Optionally, the apparatus further includes:

a second data request receiving module, configured to receive a second data acquisition request sent by the V-NWDAF, where the second data acquisition request includes: a second data analysis identifier and a second analysis target;

the second analysis data acquisition module is used for acquiring second analysis data corresponding to the second analysis identification and the second analysis target from the H-ADRF;

and the second analysis data sending module is used for sending the second analysis data to the V-NWDDAF.

Optionally, the second analysis data sending module is specifically configured to randomly obtain sample second analysis data from the second analysis data; according to a preset algorithm, inserting synthesized second analysis data into the sample second analysis data to obtain expanded data; extracting target second analysis data from the expanded data; and sending the target second analysis data to the V-NWDAF.

In a fourth aspect, an embodiment of the present application further provides a data analysis device applied to a visited network data analysis function V-NWDAF, where the device includes:

a first acquisition request receiving module, configured to receive a first data acquisition request sent by a home network data analysis function H-NWDAF, where the first data acquisition request is generated by the H-NWDAF according to a data analysis request, and the first data acquisition request includes: a first data analysis identifier and a second analysis target;

The first analysis data acquisition module is used for acquiring first analysis data corresponding to the first data analysis identifier and the second analysis target from the visiting place analysis data storage function V-ADRF according to the first data acquisition request;

and the first analysis data sending module is used for sending the first analysis data to the H-NWDAF so that the H-NWDAF performs preset analysis on the first analysis data and sends a data analysis result to the network opening function AF through the NEF.

Optionally, the first analysis data sending module is specifically configured to randomly obtain first analysis data of a sample from the first analysis data; according to a preset algorithm, inserting and synthesizing first analysis data into the first analysis data of the sample to obtain expanded data; extracting target first analysis data from the expanded data; and sending the target first analysis data to the V-NWDAF.

Optionally, the apparatus further includes:

a second analysis request receiving module, configured to receive a second data analysis request sent by the application function AF through the network open function NEF, where the second data analysis request includes: a second data analysis identifier and a second analysis target;

A second acquisition request sending module, configured to send a second data acquisition request to a network function NF or an operation maintenance management OAM, a visitor analysis data repository function V-ADRF, and the H-NWDAF, respectively, according to the second data analysis request, where the second data acquisition request includes: the second data analysis identity and the second analysis target;

a second analysis data receiving module, configured to receive second analysis data corresponding to the second analysis target and the second data analysis identifier sent by the NF or the OAM, the V-ADRF, and the H-NWDAF, where the H-NWDAF obtains the second analysis data through a home analysis data repository function H-ADRF;

and the second data analysis module is used for carrying out preset analysis on the second analysis data according to the second data analysis identification and sending a second data analysis result to the AF through the NEF.

Optionally, after the second data analysis module, the apparatus further includes:

and the second data storage module is used for storing the second analysis data and the second data analysis result sent by the NF or the OAM and the H-NWDDAF to the V-ADRF.

In a fifth aspect, an embodiment of the present invention further provides a network data analysis functional entity, including:

a transceiver, a processor, and a storage medium;

the transceiver is used for receiving and transmitting data;

the storage medium stores program instructions executable by the processor;

the processor is configured to invoke the program instructions stored in the storage medium to perform the steps of the data analysis method according to any of the first aspects or to perform the steps of the data analysis method according to any of the second aspects.

In a sixth aspect, embodiments of the present invention further provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the data analysis method according to any of the first aspects or performs the steps of the data analysis method according to any of the second aspects.

The beneficial effects of this application are:

the application provides a data analysis method and device, which realize data roaming among different public land mobile networks through communication between H-NWDAF and V-NWDAF, break through space constraint of data, avoid data resource waste caused by failure to acquire analysis data of a visiting place, and effectively improve data analysis prediction performance by acquiring a large amount of analysis data of the attribution place and the visiting place.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a data analysis system according to an embodiment of the present disclosure;

FIG. 2 is an interactive schematic diagram of a conventional data analysis method;

FIG. 3 is a flowchart illustrating a data analysis method according to an embodiment of the present disclosure;

fig. 4 is a second flow chart of a data analysis method according to an embodiment of the present application;

fig. 5 is a flowchart of a data analysis method according to an embodiment of the present application;

fig. 6 is a flow chart diagram of a data analysis method according to an embodiment of the present application;

fig. 7 is a flow chart of a data analysis method according to an embodiment of the present application;

fig. 8 is a flowchart of a data analysis method according to an embodiment of the present application;

FIG. 9 is a schematic diagram showing interactions of a data analysis method according to an embodiment of the present disclosure;

Fig. 10 is a second interaction diagram of the data analysis method according to the embodiment of the present application;

fig. 11 is a schematic structural diagram of a data analysis device according to an embodiment of the present disclosure;

fig. 12 is a schematic diagram of a second structure of the data analysis device according to the embodiment of the present application;

fig. 13 is a schematic diagram of a network data analysis functional entity according to an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention.

Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

Furthermore, the terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that, without conflict, features in embodiments of the present application may be combined with each other.

Referring to fig. 1, a schematic frame diagram of a data analysis system according to an embodiment of the present application is shown in fig. 1, where the data analysis system includes: a User Equipment (UE), a radio access Network (Radio Access Network, RAN), a User plane Function (User Plane Function, UPF), a Data Network (DN), an access and mobility management Function (access and mobility management Function, AMF), a session management Function (Session Management Function, SMF), a Network Data analysis Function (Network Data Analytics Function, NWDAF) Network element, an analysis Data repository Function (Analytics Data Repository Function, ADRF), a Data acquisition coordination Function (Data acquisition coordination Function, DCCF), a Network Function (NF), operation, administration and maintenance (Operation Administration and Maintenance, OAM), a Network opening Function (Network Exposure Function, NEF) Network element, an application Function (Application Function, AF).

The UPF, AMF, SMF, NWDAF, ADRF, DCCF, NF, OAM, NEF and the AF are core network elements, which can communicate with each other through a preset interface, and the core network elements can be independent computer devices or servers, or can be integrated in the same computer device or server to realize different functions, which is not limited in the invention.

Referring to fig. 2, an interactive schematic diagram of a conventional data analysis method is shown in fig. 2, and the process of the data analysis method may include:

s11: the UE initiates a subscription analysis request to the NEF through AF.

S12: the NEF grants the subscription analysis request of the AF and subscribes to the analysis service with the NWDAF.

S13: the NWDAF requests the NF or OAM for acquiring real-time analysis data, and the request includes a time interval for acquiring the real-time analysis data.

S14: NF or OAM periodically reports real-time analysis data to NWDAF.

S15: the NWDAF also obtains historical analysis data to the ADRF either directly or through the DCCF.

S16: the ADRF sends historical analysis data to the NWDAF either directly or through the DCCF.

S17: the NWDAF performs data analysis based on the real-time analysis data and the historical analysis data.

S18: the analysis results were returned to AF by NEF.

S19: the NWDAF stores the real-time analysis data and analysis results in the ADRF directly or through the DCCF.

When the UE is located in the H-PLMN, the home network data analysis function NWDAF, i.e., the H-NWDAF, acquires real-time analysis data from NF or OAM, acquires historical analysis data from home ADRF, i.e., the H-ADRF, and stores the real-time analysis data and the analysis result in the H-ADRF; when the UE is located in a visiting network data analysis function V-PLMN, the visiting NWDAF, namely the V-NWDAF, acquires real-time analysis data from NF or OAM, acquires historical analysis data from the visiting ADRF, namely the V-ADRF, and stores the real-time analysis data and analysis results in the V-ADRF.

Based on this, the prior art has the following technical problems: when the UE roams to a V-PLMN which is not accessed before, if the UE needs to request data analysis service in the V-PLMN, but the V-PLMN has no historical data information related to the UE, even if the V-PLMN starts to collect data after the UE is registered, the collected data is very limited, so that the analysis and prediction performance is poor; the H-PLMN accessed by the UE cannot acquire the data collected in the V-PLMN, so that the data resource is wasted to a certain extent.

Based on the problems in the prior art, the application aims to provide a data analysis method, which realizes data sharing of a home location and a visiting location through communication between H-NWDAF and V-NWDAF, breaks through spatial constraint of data and improves data analysis prediction performance.

Referring to fig. 3, a first flowchart of a data analysis method according to an embodiment of the present application is shown in fig. 3, and the method may include:

s21: receiving a first data analysis request sent by the AF through the NEF, wherein the first data analysis request comprises the following steps: the first data analysis identifies and first analysis target.

In this embodiment, the first data analysis identifier is used to indicate a first data analysis method and a first analysis data type required by the first data analysis method, and the first analysis target is used to indicate a UE to which the first analysis data needs to be acquired belongs, where the first analysis target may be a specified UE or all UEs, and the specified UE may be all UEs of the specified type.

Specifically, the UE may initiate a data analysis request for itself, or as a management terminal of multiple UEs, initiate a data analysis request for multiple UEs, and the UE initiates a first data analysis request to the NEF through the AF, where the NEF forwards the first data analysis request to the H-NWDAF where the UE is located, so as to subscribe the data analysis function to the H-NWDAF for the AF.

In one possible implementation, the first data analysis request further includes: and the identification of the AF is carried out, so that the H-NWDAF agrees with the AF subscription data analysis function according to the first data analysis request, and then the authorization data analysis function is configured for the AF according to the identification of the AF.

In one possible implementation, the first data analysis request further includes: the analysis and filtration information is used for limiting the acquired data, for example, acquiring historical data of a preset time period and the like.

S22: sending a first data acquisition request to NF or OAM, H-ADRF and V-NWDAF according to the first data analysis request, wherein the first data acquisition request comprises: the first data analysis identifies and first analysis target.

In this embodiment, for the case where the UE is in the home location, the H-NWDAF needs to obtain according to the first data analysis request: real-time analysis data generated by the UE at the attribution, historical analysis data pre-stored at the attribution and historical analysis data generated by the UE at the roaming visit place.

Specifically, the H-NWDAF sends a first data acquisition request to NF or OAM according to the first data analysis request, where the first data acquisition request includes: and acquiring a time interval of the real-time analysis data to instruct NF or OAM to periodically report the real-time analysis data to the H-NWDAF according to the time interval.

The H-NWDAF also sends a first data acquisition request to the H-ADRF according to the first data analysis request, so that the H-ADRF sends historical analysis data of the attribution to the H-NWDAF according to the first data analysis identifier and the first analysis target in the first data analysis request. Wherein the historical analysis data in the H-ADRF is that the H-NWDAF stores the real-time analysis data and the analysis result in the H-ADRF.

The H-NWDAF also sends a first data acquisition request to the V-NWDAF according to the first data analysis request, so that the V-NWDAF forwards the first data acquisition request to the V-ADRF, and the V-ADRF sends historical analysis data of the visiting place to the H-NWDAF through the V-NWDAF according to the first data analysis identifier and the first analysis target in the first data analysis request.

S23: and receiving first analysis data corresponding to the first analysis target and identified by the first data analysis identifier sent by NF or OAM, H-ADRF and V-NWDAF, wherein the V-NWDAF acquires the first analysis data through V-ADRF.

In this embodiment, the real-time analysis data of the home location sent by NF or OAM at regular time is received, the history analysis data of the home location sent by H-ADRF is received, the history analysis data of the visited location sent by V-NWDAF is received, and the real-time analysis data of the home location, the history analysis data of the home location, and the history analysis data of the visited location are used together as the first analysis data.

The historical analysis data of the attribution and the historical analysis data of the visiting place comprise: raw history data and analysis results from analyzing the raw history data.

In one possible implementation, if a DCCF is disposed between the H-NWDAF and the H-ADRF, the H-NWDAF further indirectly sends a first data acquisition request to the H-ADRF through the DCCF according to the first data analysis request, and the H-ADRF indirectly sends historical analysis data of the home location to the H-NWDAF through the DCCF.

S24: and carrying out preset analysis on the first analysis data according to the first data analysis identifier, and sending a first data analysis result to the AF through the NEF.

In this embodiment, the H-NWDAF performs data analysis on the first analysis data according to the analysis method corresponding to the first data analysis identifier, generates a first data analysis result, sends the first data analysis result to the AF through the NEF, and sends the first data analysis result to the UE through the AF.

For example, the first analysis data may be network status data of the UE, network traffic usage data of the UE, etc., and the H-NWDAF performs data analysis according to the real-time analysis data and the historical analysis data, so as to predict a network status or a network traffic usage situation of the UE in a preset time period.

In a possible implementation manner, after performing the preset analysis on the first analysis data according to the first data analysis identifier in S24 and sending the data analysis result to the AF through the NEF, the method may further include:

In this embodiment, in order to expand the richness of the historical analysis data, after the H-NWDAF performs data analysis on the first analysis data, the NF or OAM and the V-NWDAF send the first analysis data and the first data analysis result are stored in the H-ADRF, so that when the data analysis is performed next time, the H-NWDAF may acquire more abundant historical data.

According to the data analysis method provided by the embodiment, the H-NWAF realizes data roaming among different public land mobile networks by acquiring the analysis data of the attribution and the analysis data of the visiting place, breaks through the space constraint of the data, avoids the data resource waste caused by the fact that the analysis data of the visiting place cannot be acquired, and can effectively improve the data analysis prediction performance by acquiring a large amount of analysis data of the attribution and the visiting place.

One possible implementation of the H-NWDAF in response to the data acquisition request of V-NWDAF is described below in connection with fig. 4.

Referring to fig. 4, a second flow chart of the data analysis method provided in the embodiment of the present application, as shown in fig. 4, the method may further include:

s31: receiving a second data acquisition request sent by the V-NWDAF, wherein the second data acquisition request comprises: the second data analysis identifies and second analysis targets.

S32: and acquiring second analysis data corresponding to the second analysis target from the H-ADRF.

S33: the second analysis data is sent to the V-NWDAF.

In this embodiment, when the UE is at the visited place, the H-NWDAF receives a second data acquisition request sent by the V-NWDAF, where the second data acquisition request is generated by the V-NWDAF according to a second data analysis request sent by the AF through the NEF. Wherein the second data analysis identifier is used for indicating a second data analysis method and a second analysis data type required by the second data analysis method, and the second analysis target is used for indicating the UE to which the acquired second analysis data is belonged.

After the H-NWDAF receives the second data acquisition request, second analysis data is retrieved from the H-ADRF according to the second data analysis type and the second analysis target, and the retrieved second analysis data is sent to the V-NWDAF so that the V-NWDAF performs data analysis according to the second analysis data, wherein the second analysis data acquired from the H-ADRF is historical analysis data of a attribution.

In one possible implementation, if a DCCF is disposed between the H-NWDAF and the H-ADRF, the H-NWDAF indirectly sends the second data acquisition request to the H-ADRF through the DCCF, the H-ADRF indirectly sends the historical analysis data of the home location to the H-NWDAF through the DCCF, and the H-NWDAF sends the historical analysis data to the V-NWDAF.

According to the data analysis method provided by the embodiment, the H-NWDAF sends the analysis data of the attribution to the V-NWDAF according to the data acquisition request of the V-NWDAF, so that the data roaming among different public land mobile networks is realized, the space constraint of the data is broken through, the data resource waste caused by the fact that the analysis data of the visiting place cannot be acquired is avoided, and the data analysis prediction performance can be effectively improved by acquiring a large amount of analysis data of the attribution and the visiting place.

One possible implementation of the H-NWDAF transmitting the second analysis data is described below in connection with fig. 5.

Referring to fig. 5, a third flow chart of the data analysis method according to the embodiment of the present application, as shown in fig. 5, the process of sending the second analysis data to the V-NWDAF in S33 may include:

s331: sample second analysis data is randomly acquired from the second analysis data.

S332: and according to a preset algorithm, inserting and synthesizing second analysis data into the second analysis data of the sample, and obtaining the expanded data.

S333: and extracting target second analysis data from the expanded data.

S334: the target second analysis data is sent to the V-NWDAF.

In this embodiment, when the home PLMN sets a transmission right for the analysis data, that is, the H-NWDAF cannot transmit the original analysis data of the home location, it is necessary to process the original analysis data. The sending authority may be a sending authority set by the user for the data of the UE, a policy authority of an operator, or a regulatory constraint authority.

Specifically, one piece of initial second analysis data is randomly selected from the plurality of pieces of second analysis data, the euclidean distance between the initial second analysis data and the other pieces of second analysis data is calculated, and at least one piece of other second analysis data closest to the euclidean distance of the at least one piece of initial second analysis data is selected from the other pieces of second analysis data as the sample second analysis data.

And randomly inserting synthesized second analysis data between the at least one initial second analysis data and the sample second analysis data by adopting a preset random algorithm according to the at least one initial second analysis data and the sample second analysis data, and obtaining expanded data according to the plurality of second analysis data and the plurality of synthesized second analysis data. And randomly extracting a plurality of data from the expanded data to serve as target second analysis data, and sending the target second analysis data to the V-NWDAF.

In one possible implementation, a number of other second analysis data may also be randomly selected from the at least one other second analysis data as sample second analysis data.

The process of extracting the target second analysis data after data expansion from the second analysis data will be described below with reference to examples.

By way of example, the raw data stored by H-ADRF is:

n is the feature quantity, namely, the feature of multiple dimensions contained in each second analysis data reported by NF or OAM; m is a data quantity, which may be m time intervals, feature data of each time interval is mapped into a multidimensional space, and analysis data of each time interval is a vector of an n-dimensional space.

Randomly selecting one initial second analysis data x of the m second analysis data _j Respectively calculating other second analysis data x _k And the initial second analysis data x _j According to the Euclidean distance of other second analysis data x _k And the initial second analysis data x _j From other second analysis data x _k Selecting Euclidean distance from initial second analysis data x _j The nearest K analytical data, the example, euclidean distance, is calculated as:

from the distance initial second analysis data x _j Recent K analytical data x _k Randomly selecting M analysis data x _k (M.ltoreq.K) as sample second analysis data, and the initial second analysis data x _j And connecting with the sample second analysis data, and randomly selecting a point from the connecting lines of the two points as second insertion data. Illustratively, given a random number rand (0, 1) between 0 and 1, a second interpolated data is constructed by the following formula:

x _new ＝x _j +rand(0,1)×(x _k -x _j )

after the K pieces of analysis data closest to the Euclidean distance are inserted into the synthesized second analysis data, randomly extracting target second analysis data according to the second analysis data and the synthesized second analysis data.

According to the data analysis method provided by the embodiment, after the second analysis data is processed and expanded, the target second analysis data is extracted from the expanded data and sent to the V-NWDAF, so that the limitation of the analysis data in terms of user privacy and data safety is broken through, the data roaming among different public land mobile networks is realized, the space constraint of the data is broken through, the data resource waste caused by the fact that the analysis data of the visiting place cannot be acquired is avoided, and the data analysis prediction performance can be effectively improved by acquiring a large amount of analysis data of the attribution place and the visiting place.

One possible implementation of the V-NWDAF in response to the data acquisition request of the H-NWDAF is described below in connection with fig. 6.

Referring to fig. 6, a flow chart of a data analysis method provided in the embodiment of the present application is shown in fig. 6, and the method may include:

s41: receiving a first data acquisition request sent by the H-NWDAF, wherein the first data acquisition request is generated by the H-NWDAF according to a first data analysis request, and the first data acquisition request comprises: the first data analysis identifies and first analysis target.

S42: and acquiring first analysis data corresponding to the first analysis target and the first data analysis identifier from the V-ADRF according to the first data acquisition request.

S43: and sending the first analysis data to the H-NWDAF so that the H-NWDAF performs preset analysis on the first analysis data, and sending the first data analysis result to the AF through the NEF.

In this embodiment, when the UE is in the home location, the V-NWDAF receives a first data acquisition request sent by the H-NWDAF, where the first data acquisition request is generated by the H-NWDAF according to a first data analysis request sent by the AF through the NEF. The first data analysis identifier is used for indicating a first data analysis method and a first analysis data type required by the first data analysis method, and the first analysis target is used for indicating the UE to which the first analysis data needs to be acquired.

After the V-NWDAF receives the first data acquisition request, according to the first data analysis type and the first analysis target, first analysis data are retrieved from the V-ADRF, and the retrieved first analysis data are sent to the H-NWDAF so that the H-NWDAF performs data analysis according to the first analysis data, wherein the first analysis data acquired from the V-ADRF are historical analysis data of a visiting place.

In one possible implementation, if a DCCF is disposed between the V-NWDAF and the V-ADRF, the V-NWDAF indirectly sends the first data acquisition request to the V-ADRF through the DCCF, the V-ADRF indirectly sends the historical analysis data of the visited place to the V-NWDAF through the DCCF, and the V-NWDAF sends the historical analysis data to the H-NWDAF.

According to the data analysis method provided by the embodiment, the V-NWDAF sends the analysis data of the visiting place to the H-NWDAF according to the data acquisition request of the H-NWDAF, so that the data roaming among different public land mobile networks is realized, the space constraint of the data is broken through, the data resource waste caused by the fact that the analysis data of the visiting place cannot be acquired is avoided, and the data analysis prediction performance can be effectively improved by acquiring a large amount of analysis data of the attribution place and the visiting place.

One possible implementation of the V-NWDAF transmitting the first analysis data is described below in connection with fig. 7.

Referring to fig. 7, a fifth flowchart of a data analysis method according to an embodiment of the present application, as shown in fig. 7, the process of sending the first analysis data to the H-NWDAF in S43 may include:

s431: randomly acquiring sample first analysis data from the first analysis data;

s432: according to a preset algorithm, inserting and synthesizing first analysis data into the first analysis data of the sample to obtain expanded data;

s433: extracting target first analysis data from the expanded data;

s434: the target first analysis data is sent to the V-NWDAF.

In this embodiment, when the visited PLMN sets a transmission right for the analysis data, that is, the V-NWDAF cannot transmit the original analysis data of the visited PLMN, the original analysis data needs to be processed. The sending authority may be a sending authority set by the user for the data of the UE, a policy authority of an operator, or a regulatory constraint authority.

Specifically, one initial first analysis data is randomly selected from a plurality of first analysis data, the Euclidean distance between the initial first analysis data and other first analysis data is calculated, and at least one other first analysis data closest to the Euclidean distance of the at least one initial first analysis data is selected from the other first analysis data as sample first analysis data.

And randomly inserting synthesized first analysis data between the at least one initial first analysis data and the sample first analysis data by adopting a preset random algorithm according to the at least one initial first analysis data and the sample first analysis data, and obtaining expanded data according to the plurality of first analysis data and the plurality of synthesized first analysis data. And randomly extracting a plurality of data from the expanded data to serve as target first analysis data, and sending the target first analysis data to the V-NWDAF.

In one possible implementation, a number of further first analysis data may also be randomly selected from the at least one further first analysis data as sample first analysis data.

The example of generating the synthesized first analysis data may refer to the foregoing example of generating the synthesized second analysis data, which is not described herein.

According to the data analysis method provided by the embodiment, after the first analysis data is processed and expanded, the target first analysis data is extracted from the expanded data and sent to the H-NWDAF, so that the limitation of the analysis data in terms of user privacy and data safety is broken through, the data roaming among different public land mobile networks is realized, the space constraint of the data is broken through, the data resource waste caused by the fact that the analysis data of the visiting place cannot be acquired is avoided, and the data analysis prediction performance can be effectively improved by acquiring a large amount of analysis data of the attribution place and the visiting place.

One possible implementation of the V-NWDAF to obtain the analysis data according to the data analysis request is described below in connection with fig. 8.

Referring to fig. 8, a flowchart of a data analysis method provided in an embodiment of the present application is shown in fig. 8, where the method may further include:

s51: receiving a second data analysis request sent by the AF through the NEF, wherein the second data analysis request comprises: the second data analysis identifies and second analysis targets.

In this embodiment, the second data analysis identifier is used to indicate the second data analysis method and a second analysis data type required by the second data analysis method, and the second analysis target is used to indicate the UE to which the second analysis data needs to be acquired belongs, where the second analysis target may be a designated UE or all UEs, and the designated UE may be all UEs of the designated type.

S52: sending a second data acquisition request to NF or OAM, V-ADRF and H-NWDAF, respectively, according to the second data analysis request, the second data acquisition request comprising: the second data analysis identifies and second analysis targets.

In this embodiment, for the case that the UE is in the visited place, the V-NWDAF needs to acquire according to the second data analysis request: real-time analysis data generated by the UE at the visiting place, history analysis data pre-stored at the visiting place and history analysis data generated by the UE at the attribution place.

Specifically, the V-NWDAF sends a second data acquisition request to NF or OAM according to the second data analysis request, where the second data acquisition request includes: and acquiring a time interval of the real-time analysis data to instruct NF or OAM to periodically report the real-time analysis data to the V-NWDAF according to the time interval.

The V-NWDAF also sends a second data acquisition request to the V-ADRF according to the second data analysis request, so that the V-ADRF sends historical analysis data of the visiting place to the V-NWDAF according to the second data analysis identifier and the second analysis target in the second data analysis request. Wherein the historical analysis data in the V-ADRF is that the V-NWDAF stores the real-time analysis data and the analysis result in the V-ADRF.

The V-NWDAF also sends a second data acquisition request to the H-NWDAF according to the second data analysis request, so that the H-NWDAF forwards the second data acquisition request to the H-ADRF, and the H-ADRF sends the historical analysis data of the attribution to the V-NWDAF through the H-NWDAF according to the second data analysis identifier and the second analysis target in the second data analysis request.

S53: and receiving second analysis data corresponding to the second analysis target and sent by NF or OAM, V-ADRF and H-NWDAF, wherein the H-NWDAF acquires the second analysis data through H-ADRF.

In this embodiment, the real-time analysis data of the visiting place, which is sent by NF or OAM at regular time, is received, the history analysis data of the visiting place, which is sent by V-ADRF, the history analysis data of the home place, which is sent by H-NWDAF, are received, and the real-time analysis data of the visiting place, the history analysis data of the visiting place, and the history analysis data of the home place are used together as the second analysis data.

The historical analysis data of the visiting place and the historical analysis data of the attribution place comprise: raw history data and analysis results from analyzing the raw history data.

In one possible implementation, if a DCCF is disposed between the V-NWDAF and the V-ADRF, the V-NWDAF further indirectly sends a second data acquisition request to the V-ADRF through the DCCF according to the second data analysis request, and the V-ADRF indirectly sends the historical analysis data of the visited place to the V-NWDAF through the DCCF.

S54: and carrying out preset analysis on the second analysis data according to the second data analysis identifier, and sending a second data analysis result to the AF through the NEF.

In this embodiment, the V-NWDAF performs data analysis on the second analysis data according to the analysis method corresponding to the second data analysis identifier, generates a second data analysis result, sends the second data analysis result to the AF through the NEF, and sends the second data analysis result to the UE through the AF.

For example, the second analysis data may be network status data of the UE, network traffic usage data of the UE, and the like, and the V-NWDAF performs data analysis according to the real-time analysis data and the historical analysis data, so as to predict a network status or a network traffic usage situation of the UE in a preset time period.

In a possible implementation manner, after performing the preset analysis on the second analysis data according to the second data analysis identifier in S54 and sending the data analysis result to the AF through the NEF, the method may further include:

and storing the second analysis data and the second data analysis result sent by the NF or the OAM and the H-NWDAF to the V-ADRF.

In this embodiment, in order to expand the richness of the historical analysis data, after the V-NWDAF performs data analysis on the second analysis data, the second analysis data and the second data analysis result sent by NF or OAM and H-NWDAF are stored in the V-ADRF, so that when the data analysis is performed next time, more abundant historical data can be obtained.

According to the data analysis method provided by the embodiment, the V-NWDAF realizes data roaming among different public land mobile networks by acquiring the analysis data of the attribution and the analysis data of the visiting place, breaks through the space constraint of the data, avoids the data resource waste caused by the fact that the analysis data of the visiting place cannot be acquired, and can effectively improve the data analysis prediction performance by acquiring a large amount of analysis data of the attribution and the visiting place.

Referring to fig. 9, an interaction diagram of a data analysis method provided in an embodiment of the present application is shown in fig. 9, where the data analysis method includes:

s61: the AF sends a first data analysis request to the H-NWDAF through the NEF.

S62: the H-NWDAF sends a first data acquisition request to NF or OAM, H-ADRF and V-NWDAF.

S63: the V-NWDAF sends a first data acquisition request to the V-ADRF.

S64: the V-ADRF sends the first analysis data to the V-NWDAF.

S64: first analysis data sent by NF or OAM, H-ADRF and V-NWDAF are received.

S65: and analyzing the first analysis data to generate a first data analysis result.

S66: the first data analysis result is sent to the AF through the NEF.

Referring to fig. 10, a second interaction diagram of the data analysis method provided in the embodiment of the present application, as shown in fig. 10, includes:

s71: the AF sends a second data analysis request to the V-NWDAF via NEF.

S72: the V-NWDAF sends a second data acquisition request to NF or OAM, V-ADRF, and H-NWDAF.

S73: the H-NWDAF sends a second data acquisition request to the H-ADRF.

S74: the H-ADRF sends second analysis data to the H-NWDAF.

S74: and receiving second analysis data sent by NF or OAM, V-ADRF and H-NWDAF.

S75: and analyzing the second analysis data to generate a second data analysis result.

S76: and sending the second data analysis result to the AF.

On the basis of the embodiment, the embodiment of the application also provides a data analysis device which is applied to the H-NWDAF. Referring to fig. 11, a first structural diagram of a data analysis device according to an embodiment of the present application is shown in fig. 11, where the device includes:

a first analysis request receiving module 11, configured to receive a first data analysis request sent by the application function AF through the network open function NEF, where the first data analysis request includes: a first data analysis identifier and a first analysis target;

a first acquisition request sending module 12, configured to send a first data acquisition request to the network function NF or the operation maintenance management OAM, the home location analysis data repository function H-ADRF, and the visited network data analysis function V-NWDAF according to the first data analysis request, where the first data acquisition request includes: a first data analysis identifier and a first analysis target;

the first analysis data receiving module 13 is configured to receive first analysis data corresponding to a first analysis target and a first data analysis identifier sent by NF or OAM, H-ADRF, and V-NWDAF, where the V-NWDAF obtains the first analysis data through a visitor analysis data repository function V-ADRF;

The first data analysis module 14 is configured to perform preset analysis on the first analysis data according to the first data analysis identifier, and send the data analysis result to the AF through the NEF.

Optionally, after the first data analysis module 14, the apparatus further comprises:

and the first data storage module is used for storing the first analysis data and the first data analysis result sent by the NF or the OAM and the V-NWDAF to the H-ADRF.

Optionally, the apparatus further comprises:

and the second analysis data transmission module is used for transmitting the second analysis data to the V-NWDAF.

Optionally, the second analysis data sending module is specifically configured to randomly obtain sample second analysis data from the second analysis data; according to a preset algorithm, inserting and synthesizing second analysis data into the second analysis data of the sample to obtain expanded data; extracting target second analysis data from the expanded data; the target second analysis data is sent to the V-NWDAF.

On the basis of the embodiment, the embodiment of the application also provides a data analysis device which is applied to the V-NWDAF. Referring to fig. 12, a second schematic structural diagram of a data analysis device according to an embodiment of the present application is shown in fig. 12, where the device includes:

a first acquisition request receiving module 21, configured to receive a first data acquisition request sent by the home network data analysis function H-NWDAF, where the first data acquisition request is generated by the H-NWDAF according to the data analysis request, and the first data acquisition request includes: a first data analysis identifier and a second analysis target;

a first analysis data acquisition module 22, configured to acquire, according to the first data acquisition request, first analysis data corresponding to the first data analysis identifier and the second analysis target from the visited analysis data repository function V-ADRF;

the first analysis data sending module 23 is configured to send the first analysis data to the H-NWDAF, so that the H-NWDAF performs a preset analysis on the first analysis data, and send the data analysis result to the AF through the NEF.

Optionally, the first analysis data sending module 23 is specifically configured to randomly obtain first analysis data of the sample from the first analysis data; according to a preset algorithm, inserting and synthesizing first analysis data into the first analysis data of the sample to obtain expanded data; extracting target first analysis data from the expanded data; the target first analysis data is sent to the V-NWDAF.

Optionally, the apparatus further comprises:

the second analysis request receiving module is configured to receive a second data analysis request sent by the application function AF through the network open function NEF, where the second data analysis request includes: a second data analysis identifier and a second analysis target;

the second acquisition request sending module is configured to send a second data acquisition request to the network function NF or the operation maintenance management OAM, the visitor analysis data repository functions V-ADRF and H-NWDAF, respectively, according to the second data analysis request, where the second data acquisition request includes: a second data analysis identifier and a second analysis target;

the second analysis data receiving module is used for receiving second analysis data corresponding to a second analysis target and a second data analysis identifier sent by NF or OAM, V-ADRF and H-NWDAF, wherein the H-NWDAF acquires the second analysis data through a home analysis data storage function H-ADRF;

and the second data analysis module is used for carrying out preset analysis on the second analysis data according to the second data analysis identifier and sending a second data analysis result to the AF through the NEF.

Optionally, after the second data analysis module, the apparatus further comprises:

and the second data storage module is used for storing the second analysis data and the second data analysis result sent by the NF or the OAM and the H-NWDAF to the V-ADRF.

The foregoing apparatus is used for executing the method provided in the foregoing embodiment, and its implementation principle and technical effects are similar, and are not described herein again.

The above modules may be one or more integrated circuits configured to implement the above methods, for example: one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASICs), or one or more microprocessors, or one or more field programmable gate arrays (Field Programmable Gate Array, abbreviated as FPGAs), etc. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

Referring to fig. 13, a schematic diagram of a network data analysis functional entity provided in an embodiment of the present application, as shown in fig. 13, the network data analysis functional entity 100 includes: a transceiver 101, a processor 102, and a storage medium 103; the transceiver 101 is used for receiving and transmitting data; the storage medium 103 stores program instructions executable by the processor 102; the processor 102 is configured to call program instructions stored in the storage medium 103 to perform steps of a data analysis method as applied to H-NWDAF or to perform steps of a data analysis method as applied to V-NWDAF.

In an embodiment, a computer-readable storage medium is also provided, on which a computer program is stored which, when being executed by a processor, performs steps of a data analysis method as applied to H-NWDAF, or performs steps of a data analysis method as applied to V-NWDAF.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.

The integrated units implemented in the form of software functional units described above may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (english: processor) to perform some of the steps of the methods according to the embodiments of the invention. And the aforementioned storage medium includes: u disk, mobile hard disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

The foregoing is merely illustrative of embodiments of the present invention, and the present invention is not limited thereto, and any changes or substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and the present invention is intended to be covered by the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims

1. A data analysis method applied to a home network data analysis function H-NWDAF, the method comprising:

2. The method of claim 1, wherein the pre-set analysis is performed on the first analysis data according to the first data analysis identifier, and after the data analysis result is sent to the AF through the NEF, the method further comprises:

3. The method of claim 1, wherein the method further comprises:

and sending the second analysis data to the V-NWDAF.

4. The method of claim 3, wherein said sending the second analysis data to the V-NWDAF comprises:

randomly acquiring sample second analysis data from the second analysis data;

extracting target second analysis data from the expanded data;

and sending the target second analysis data to the V-NWDAF.

5. A data analysis method, characterized in that it is applied to a visited network data analysis function V-NWDAF, the method comprising:

and sending the first analysis data to the H-NWDAF so that the H-NWDAF performs preset analysis on the first analysis data, and sending a first data analysis result to the AF through a network opening function NEF.

6. The method of claim 5, wherein said transmitting said first analysis data to said H-NWDAF comprises:

randomly acquiring sample first analysis data from the first analysis data;

extracting target first analysis data from the expanded data;

and sending the target first analysis data to the V-NWDAF.

7. The method of claim 5, wherein the method further comprises:

8. The method of claim 7, wherein after the receiving the second data analysis identifier sent by the NF or the OAM, the V-ADRF, and the H-NWDAF and the second analysis data corresponding to the second analysis target, the method further comprises:

9. A data analysis apparatus for application to a home network data analysis function H-NWDAF, the apparatus comprising:

And the first data analysis module is used for carrying out preset analysis on the first analysis data according to the first data analysis identifier and sending a first data analysis result to the AF through the NEF.

10. A data analysis device for application to a visitor network data analysis function V-NWDAF, the device comprising:

a first acquisition request receiving module, configured to receive a first data acquisition request sent by a home network data analysis function H-NWDAF, where the first data acquisition request is generated by the H-NWDAF according to a first data analysis request, and the first data acquisition request includes: a first data analysis identifier and a first analysis target;

the first analysis data acquisition module is used for acquiring first analysis data corresponding to the first data analysis identifier and the first analysis target from the visiting place analysis data storage function V-ADRF according to the first data acquisition request;

and the first analysis data sending module is used for sending the first analysis data to the H-NWDAF so that the H-NWDAF performs preset analysis on the first analysis data and sends a first data analysis result to the AF through a network opening function NEF.